S_R

功能：应用Rudin-Osher-Fatemi模型进行图像去噪，在ROFtest.m 中输入图像，附带文档ROFscheme内容为此模型的数值分析过程，比较详细，适合初学者(Classic 􏰉 Rudin-Osher-Fatemi model denoising, the including documentation is the numerical analysis process of the model in detail, suitable for beginners)

共有5个代码其中4个分别实现图像的中值滤波、均值滤波、双边滤波、Lee滤波，另一个是求图像的均值和方差。模板均不固定自己根据需要确定合适的w值。(There are five codes of which four were achieved image median filter, mean filter, bilateral filter, Lee filter, and the other is seeking an image of the mean and variance. Templates are not fixed ourselves w appropriate values as needed.)

最经典之做，保证别人没有上传过 实现文章 “GrabCut" Interactive Foreground Extraction using Iterated Graph Cuts 用graphcut实现图像分割，效果非常好(The most classic to do to ensure that other people do not realize uploaded article GrabCut Interactive Foreground Extraction using Iterated Graph Cuts with graphcut realize image segmentation, has very good results)

说明：  基于matlab的简单手势识别代码，初学者可自行下载。(Simple gesture recognition code, beginners can download.)

求解分线性脉冲传输方程的SSFM方法,其中使用了改进的分步傅里叶算法，适合新手(the SSFM method to calculate the nonlinear pulse propagation equation)

说明：  二值化程序：实现自适应二值化。效果较好，二值化后图片较清晰(Binarization process: the realization of adaptive binarization. Better, after binarization clearer picture)

信号进行EEMD分，作为希尔伯特黄变换的基础(try to decompose signal using EEMD，which as the Hilbert Huang Transtion basis)

该VC++程序是基于CUDA架构的中值滤波程序，GPU加速，并且使用了opencv函数库(The VC++ program is based on the CUDA architecture median filtering program, GPU acceleration, and use the opencv library)

说明：  Donoho提出的小波阀值去噪的基本思想是将信号通过小波变换（采用Mallat算法）后，信号产生的小波系数含有信号的重要信息，将信号经小波分解后小波系数较大，噪声的小波系数较小，并且噪声的小波系数要小于信号的小波系数，通过选取一个合适的阀值，大于阀值的小波系数被认为是有信号产生的，应予以保留，小于阀值的则认为是噪声产生的，置为零从而达到去噪的目的。尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点。(The basic idea of wavelet threshold de-noising proposed by Donoho is that the wavelet coefficients generated by the signal after passing through the wavelet transform (Mallat algorithm) contain the important information of the signal. After the wavelet decomposition, the wavelet coefficients of the signal are larger, the wavelet coefficients of the noise are smaller, and the wavelet coefficients of the noise are smaller than the wavelet coefficients of the signal. By selecting a suitable threshold, the wavelet coefficients of the noise are larger than the valve The wavelet coefficients of values are considered to be generated by signals, which should be preserved. The ones less than the threshold are considered to be generated by noise, which is set to zero to achieve the purpose of denoising.)

这是我的图形学的作业，实现光线跟踪。也是学别人做的，仅供学习用。(this is a study work about computer graphics , realizing tracking )